Previous works have made simple corrections to \(\beta \) -VAE or GAN model, adding some useful terms for solving disentanglement. In our work, we fully consider the disentanglement problem from information theory and then establish the BHiVAE model. Information theory and optimal coding theory [1]}, [2]} have shown that longer code can express more information. So in our model, instead of using only one dimension node to represent a ground-truth factor as in previous work, we choose multiple neural nodes to do so.
